A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g., electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged Auto-Mutual Information Clustering (LAMIC) and Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

@conference{Daly2013HCI,
title = {Brain-computer interfacing for users with Cerebral palsy, challenges and opportunities},
author = {Ian Daly and Martin Billinger and Reinhold Scherer and Gernot Muller-Putz},
url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/draft_1-1.pdf},
doi = {10.1007/978-3-642-39188-0_67},
isbn = {978-3-642-39187-3},
year = {2013},
date = {2013-07-21},
booktitle = {Lecture notes in computer science, 7th International Conference, UAHCI 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013, Proceedings, Part I},
journal = {Lecture notes in computer science},
pages = {623-632},
publisher = {Springer},
abstract = {It has been proposed that hybrid Brain-computer interfaces (hBCIs) could benefit individuals with Cerebral palsy (CP). To this end we review the results of two BCI studies undertaken with a total of 20 individuals with CP to determine if individuals in this user group can achieve BCI control.
Large performance differences are found between individuals. These are investigated to determine their possible causes. Differences in subject characteristics are observed to significantly relate to BCI performance accuracy. Additionally, significant relationships are also found between some subject characteristics and EEG components that are important for BCI control. Therefore, it is suggested that knowledge of individual users may guide development towards overcoming the challenges involved in providing BCIs that work well for individuals with CP.},
keywords = {BCI, Cerebral palsy, ERD, ERP, SVEP, Tools},
pubstate = {published},
tppubtype = {conference}
}

It has been proposed that hybrid Brain-computer interfaces (hBCIs) could benefit individuals with Cerebral palsy (CP). To this end we review the results of two BCI studies undertaken with a total of 20 individuals with CP to determine if individuals in this user group can achieve BCI control.
Large performance differences are found between individuals. These are investigated to determine their possible causes. Differences in subject characteristics are observed to significantly relate to BCI performance accuracy. Additionally, significant relationships are also found between some subject characteristics and EEG components that are important for BCI control. Therefore, it is suggested that knowledge of individual users may guide development towards overcoming the challenges involved in providing BCIs that work well for individuals with CP.

In this paper, we propose a standardized interface called TiA (TOBI interface A) to transmit raw biosignals, supporting multirate and block-oriented transmission of different kinds of signals from various acquisition devices (e.g., EEG, electrooculogram, near-infrared spectroscopy signals, etc.) at the same time. To facilitate a distinction between those kinds of signals, so-called signal types are introduced. TiA is a single-server, multiple-client system, whereby clients can connect to the server at runtime. Information transfer between client and server is divided into control and data connections. The control connections use transmission control protocol (TCP) and transmit extensible-markup-language (XML)-encoded meta information. The data transmission utilizes a user datagram protocol (UDP) or TCP with a binary data stream. A standardized handshaking procedure for the connection setup and a standardized binary data packet has been defined. Thus, a standardized layer, abstracting used hardware devices and facilitating distributed raw data transmission in a standardized way, has been evolved. A cross-platform library, implemented in C ++, is available for download.